How AI Can Predict Talent Retention Risk

Talent Retention Risk prediction, introduced by ENGAGE, is a new measure of volatility that reveals whether workers in an industry as well as in individual companies are more or less likely than average to be interested in exploring other jobs. Here’s more.

October 24, 2018 – Talent retention is critically important for all organizations for two primary reasons: Employee turnover is expensive, and top performers drive business performance. Even the best leaders have a hard time keeping top talent, especially in this current war for talent.

According to the Bureau of Labor Statistics, about three million Americans quit their jobs each month. That level of voluntary turnover speaks to the magnitude of the retention issues many organizations face today in this bullish market. HR leaders are aware of the importance of employee retention and consider it one of their most important issues. Despite the attention, progress for many organizations is limited due to competing priorities and lack of technology and data available on the actual reasons.

“Although these employee retention statistics may seem alarming at the surface, it’s not all bad news,” said Joseph Hanna, CEO of ENGAGE Talent. “Understanding what drives employee behavior and working to cultivate a stellar work environment and employee value proposition will go a long way towards helping your organization manage their retention goals.”

Predicting Talent Retention

Talent Retention Risk (TRR) prediction, introduced by ENGAGE, is a new measure of volatility versus stability that reveals whether workers in an industry as well as in individual companies are more or less likely than average to be interested in exploring other jobs.

TRR predictions are powerful given their effectiveness for evaluating many key workforce planning issues, including:

  • Is an industry at high or low risk of losing talent in the short and medium terms?
  • Is your company at higher or lower risk than other companies in your industry of losing talent?

  • How confident can you be that you can recruit away talent from competitors within your industry at reasonable cost?
  • Which competitors within your industry are you likely to have best success recruiting candidates away from?

Related: Game Changing Assessment Tools Coming to a Recruiter Near You

  • How much should you focus on targeting candidates from outside your industry in your recruiting efforts?

“We perform talent retention risk assessments for millions of companies using purely external data,” said Mr. Hanna. “The results from this assessment can be an essential tool for talent acquisition professionals because they can target candidates from organizations that have higher than average talent retention risk in their industry. Internal HR managers can also use talent retention assessments to understand how they stack up against their industry peers when it comes to keeping the best performers.”

Assessing Talent Retention

Many factors can lead to low talent retention, but the biggest challenge revolves around business shocks and events that impact employees’ job security. “Different types of events impact employees in different ways based on their function, level and location,” Mr. Hanna said. “Different events also have a different impact profile over time. A few examples of such business shocks include litigation events, M&A activity, leadership changes and data breaches.”

Recruiters Face a Threat from Automation
There’s no reason to expect that recruiters will be immune from automation . Mr. Hanna’s firm is on a journey to solve a relatively difficult data and artificial intelligence challenge that’s cropped up and is now seen as one of the most pressing dilemmas of 21st century hiring: predicting people’s job security.

After continually monitoring the Talent Retention Risk predictions of some of the biggest companies in the U.S., ENGAGE saw some similar trends across each of them – as TRR increases, the market performance tends to suffer.

Related: Five Ways HR Can Maximize Data and Analytics

ENGAGE looked at large enterprise organizations including Equifax, GE and Amazon and compared those results to what they saw at Tesla.

“With Equifax, our predictive models showed a high talent retention risk almost six weeks before a data breach at the company was publicly announced. At GE, the same was observed well before the company’s divestures and restrictions news were made public. On the other hand, the models have shown that Amazon has been consistently decreasing retention risk over the past 12 months.”

But Tesla’s TRR prediction was more drastic and telling. According to ENGAGE, the models started predicting that Tesla would have a retention problem almost 10 weeks before a nine percent layoff was announced and Elon Musk made it public via twitter.

ENGAGE uses different AI techniques to predicted retention risk, with an ensemble of models examining how various factors contribute to volatility or stability. The models were trained using a comprehensive data set covering 40 million professionals. Factors that are considered in the calculations include: Macroeconomic trends; social and news sentiment; stock performance and analyst assessments (for public companies); trends of the employer reviews and ratings; leadership changes; employee churn trends; material being consumed and shared by people from these companies and industries; and any other number of other factors that impact workforce job security.

Related: An Inside Look at Recruiting in the Big Data Sector

Contributed by Scott A. Scanlon, Editor-in-Chief; Dale M. Zupsansky, Managing Editor; Stephen Sawicki, Managing Editor; and Andrew W. Mitchell, Managing Editor – Hunt Scanlon Media

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